Presently, there exists a plurality of services that offer a vast variety of utilities that assist a user in searching the Internet for information. Typically, this information is delivered from a search engine, operated by the service, to a web browser located on a user's computing device in the form of search results. These search results are often similarly formatted within a search-results page and fail to address and/or advance an underlying task that the user is seeking to accomplish.
Increasingly, users conduct searches to accomplish “tasks,” such as reserving a table at a restaurant, renting an online movie, purchasing a book, or booking a trip. These tasks can be performed in association with various entities (e.g., people, places, and things) or various actions (e.g., buy, sell, rent, and the like). For example, during the course of a search session, the user's pending task may be general in nature, such as planning a trip or ordering a pizza. Or, the task may be refined by involving specific entities and/or actions, such as specifying parameters of an entity (e.g., limiting the search context to cameras less than $200, finding flights into only San Francisco, or purchasing an original movie released in 2005 and not the 2009 remake) or specifying an action related to the entity (e.g., renting a movie as opposed to buying).
When a user is attempting to carry out a task, conventional search engines only provide the user a laborious requirement that demands that the user actively tag items within the search session if they are to be stored and recalled at a later point in time. By way of example, the tagged items may be used to compile a list (e.g., where tags may be selected for links to goods that can be compiled into a registry for a wedding). Because most users fail to take the time to actively tag items, these requirements of conventional search engines result in both a poor user search experience and a failure of the conventional search engines to optimally recognize the user's searching intent.
Accordingly, a system for implicitly gleaning the user's searching intent during a search session, without requiring explicit user feedback that particularly specifies a current task, and for surfacing features that are specific to the user's task would provide a way for the system to showcase its understanding of the user's searching intent and to assist in advancing the goal(s) of the pending task.